Headwaters are critical reservoirs of microbial diversity for fluvial networks

Streams and rivers form conspicuous networks on the Earth and are among nature's most effective integrators. Their dendritic structure reaches into the terrestrial landscape and accumulates water and sediment en route from abundant headwater streams to a single river mouth. The prevailing view over the last decades has been that biological diversity also accumulates downstream. Here, we show that this pattern does not hold for fluvial biofilms, which are the dominant mode of microbial life in streams and rivers and which fulfil critical ecosystem functions therein. Using 454 pyrosequencing on benthic biofilms from 114 streams, we found that microbial diversity decreased from headwaters downstream and especially at confluences. We suggest that the local environment and biotic interactions may modify the influence of metacommunity connectivity on local biofilm biodiversity throughout the network. In addition, there was a high degree of variability in species composition among headwater streams that could not be explained by geographical distance between catchments. This suggests that the dendritic nature of fluvial networks constrains the distributional patterns of microbial diversity similar to that of animals. Our observations highlight the contributions that headwaters make in the maintenance of microbial biodiversity in fluvial networks

Dynamic species classification of microorganisms across time, abiotic and biotic environments-A sliding window approach.

The development of video-based monitoring methods allows for rapid, dynamic and accurate monitoring of individuals or communities, compared to slower traditional methods, with far reaching ecological and evolutionary applications. Large amounts of data are generated using video-based methods, which can be effectively processed using machine learning (ML) algorithms into meaningful ecological information. ML uses user defined classes (e.g. species), derived from a subset (i.e. training data) of video-observed quantitative features (e.g. phenotypic variation), to infer classes in subsequent observations. However, phenotypic variation often changes due to environmental conditions, which may lead to poor classification, if environmentally induced variation in phenotypes is not accounted for. Here we describe a framework for classifying species under changing environmental conditions based on the random forest classification. A sliding window approach was developed that restricts temporal and environmentally conditions to improve the classification. We tested our approach by applying the classification framework to experimental data. The experiment used a set of six ciliate species to monitor changes in community structure and behavior over hundreds of generations, in dozens of species combinations and across a temperature gradient. Differences in biotic and abiotic conditions caused simplistic classification approaches to be unsuccessful. In contrast, the sliding window approach allowed classification to be highly successful, as phenotypic differences driven by environmental change, could be captured by the classifier. Importantly, classification using the random forest algorithm showed comparable success when validated against traditional, slower, manual identification. Our framework allows for reliable classification in dynamic environments, and may help to improve strategies for long-term monitoring of species in changing environments. Our classification pipeline can be applied in fields assessing species community dynamics, such as eco-toxicology, ecology and evolutionary ecology

Breast cancer: Pretreatment drug resistance parameters (GSH-system, ATase, P-glycoprotein) in tumor tissue and their correlation with clinical and prognostic characteristics

Background: The identification of new factors predicting relapse, outcome and response to systemic therapy in breast cancer is warranted. The measurement of biological markers such as drug resistance parameters (DRPs), which are part of the phenotype of malignant cells and contribute to resistance to anti-cancer drugs may be a possibility, which may ultimately lead to improvement of therapeutic results. Patients and methods: The level of glutathione (GSH), activities of glutathione-S-transferase (GST), glutathione-peroxidase (GPx), 06-alkylguanine-DNA-alkyltransferase (ATase), and P-glycoprotein (PGP) were measured in tumor and adjacent tumor free tissue samples from 89 consecutive, untreated females with breast cancer and correlated with clinical and prognostic factors. Early breast cancer (EBC) was diagnosed in 56 patients, 22 patients had locally advanced (LABC) and 11 patients metastatic breast cancer. Results: All DRPs showed significantly higher expression in tumor than in tumor free tissues. GPx was positively correlated with GST (r = 0.3, P = 0.0048) and with GSH (r = 0.5, P = 0.0001) in tumor as well as in normal tissue. GST activity was significantly higher in EBC than in LABC or metastatic breast cancer (P = 0.02). GSH level was significantly higher in grade I than in grade 2 or grade 3 tumors (P = 0.01). When clinical characteristics were related to the level of DRP, ‘high' GSH was associated with age >60 years (P = 0.01) in EBC, and with grade 1-2 tumors (P = 0.05) in LABC. No differences in OS were apparent between groups of ‘high' and ‘low' DRP-expression. However, the four-year estimated disease-free survival of EBC tended to be higher in patients with ‘high' GST (P = 0.10) and of LABC in patients with ‘high' GPx levels (P = 0.06). Conclusion: We conclude that ‘high' levels of DRP in tumor tissue of breast cancer patients are part of the initial phenotype of the malignant cells. Due to its high prevalence (83% in EBC, 100% in primarily metastatic breast cancer), PGP did not add to prognostic information. High levels of GSH, GST and and GPx were associated with favorable clinical characteristics and good prognosis, whereas low levels of GSH and GST activity were associated with more aggressive or more advanced diseas

Generation and application of river network analogues for use in ecology and evolution

Several key processes in freshwater ecology are governed by the connectivity inherent to dendritic river networks. These have extensively been analyzed from a geomorphological and hydrological viewpoint, yet structures classically used in ecological modeling have been poorly representative of the structure of real river basins, often failing to capture well-known scaling features of natural rivers. Pioneering work identified optimal channel networks (OCNs) as spanning trees reproducing all scaling features characteristic of natural stream networks worldwide. While OCNs have been used to create landscapes for studies on metapopulations, biodiversity, and epidemiology, their generation has not been generally accessible. Given the increasing interest in dendritic riverine networks by ecologists and evolutionary biologists, we here present a method to generate OCNs and, to facilitate its application, we provide the R-package OCNet. Owing to the stochastic process generating OCNs, multiple network replicas spanning the same surface can be built; this allows performing computational experiments whose results are irrespective of the particular shape of a single river network. The OCN construct also enables the generation of elevational gradients derived from the optimal network configuration, which can constitute three-dimensional landscapes for spatial studies in both terrestrial and freshwater realms. Moreover, the package provides functions that aggregate OCNs into an arbitrary number of nodes, calculate several descriptors of river networks, and draw relevant network features. We describe the main functionalities of the package and its integration with other R-packages commonly used in spatial ecology. Moreover, we exemplify the generation of OCNs and discuss an application to a metapopulation model for an invasive riverine species. In conclusion, OCNet provides a powerful tool to generate realistic river network analogues for various applications. It thereby allows the design of spatially realistic studies in increasingly impacted ecosystems and enhances our knowledge on spatial processes in freshwater ecology in general

The Influence of Age on the Dynamic Relationship Between End-Tidal Sevoflurane Concentrations and Bispectral Index

BACKGROUND: Age is an important determinant of the pharmacokinetic profile of inhaled anesthetics. The influence of age on the dynamic profile of sevoflurane's effect has not been well described. We performed this study to characterize the influence of age and other covariates on the dynamic relationship between sevoflurane end-tidal concentration (C(ET)) and its effect measured by bispectral index (BIS). METHODS: Fifty patients, aged 3-71 yr, scheduled for minor surgery were prospectively studied. The BIS and sevoflurane C(ET) were continuously measured during the study period. During maintenance of anesthesia and after stable BIS values of 60-65 were obtained, the inspired concentration of sevoflurane was increased to 5 vol % for 5 min or until BIS <40 and then decreased. The dynamic relationship between sevoflurane C(ET) and its effect as measured by BIS during this transition period were modeled with an inhibitory E(max) model using a population pharmacokinetic-pharmacodynamic approach with NONMEM V. A predictive check method was used to validate the final model. RESULTS: The sensitivity to sevoflurane's effect as measured by BIS expressed in the C(50) [steady-state C(ET) eliciting half of maximum response (I(max))] increased with age. The speed of change of sevoflurane's effect, expressed as the effect-site equilibration half-life (t(1/2) k(e0)), increased at older ages. The predictive check analysis confirmed the adequacy of the model. CONCLUSIONS: Age significantly affects the dynamic relationship between sevoflurane C(ET) and its effect measured with BIS

Advances in the Surface Passivation of Silicon Solar Cells

AbstractThe surface passivation properties of aluminium oxide (Al2O3) on crystalline Si are compared with the traditional passivation system of silicon nitride (SiNx). It is shown that Al2O3 has fundamental advantages over SiNx when applied to the rear of p-type silicon solar cells as well as to the p+ emitter of n-type silicon solar cells. Special emphasis is paid to the transfer of Al2O3 into industrial solar cell production. We compare different Al2O3 deposition techniques suitable for mass production such as ultrafast spatial atomic layer deposition, inline plasma-enhanced chemical vapour deposition and reactive sputtering. Finally, we review the most recent cell results with Al2O3 passivation and give a brief outlook on the future prospects of Al2O3 in silicon solar cell production

Catchment-based sampling of river eDNA integrates terrestrial and aquatic biodiversity of alpine landscapes.

Monitoring of terrestrial and aquatic species assemblages at large spatial scales based on environmental DNA (eDNA) has the potential to enable evidence-based environmental policymaking. The spatial coverage of eDNA-based studies varies substantially, and the ability of eDNA metabarcoding to capture regional biodiversity remains to be assessed; thus, questions about best practices in the sampling design of entire landscapes remain open. We tested the extent to which eDNA sampling can capture the diversity of a region with highly heterogeneous habitat patches across a wide elevation gradient for five days through multiple hydrological catchments of the Swiss Alps. Using peristaltic pumps, we filtered 60 L of water at five sites per catchment for a total volume of 1800 L. Using an eDNA metabarcoding approach focusing on vertebrates and plants, we detected 86 vertebrate taxa spanning 41 families and 263 plant taxa spanning 79 families across ten catchments. For mammals, fishes, amphibians and plants, the detected taxa covered some of the most common species in the region according to long-term records while including a few more rare taxa. We found marked turnover among samples from distinct elevational classes indicating that the biological signal in alpine rivers remains relatively localised and is not aggregated downstream. Accordingly, species compositions differed between catchments and correlated with catchment-level forest and grassland cover. Biomonitoring schemes based on capturing eDNA across rivers within biologically integrated catchments may pave the way toward a spatially comprehensive estimation of biodiversity

Diversity and distribution of freshwater amphipod species in Switzerland (Crustacea: Amphipoda).

Amphipods are key organisms in many freshwater systems and contribute substantially to the diversity and functioning of macroinvertebrate communities. Furthermore, they are commonly used as bioindicators and for ecotoxicological tests. For many areas, however, diversity and distribution of amphipods is inadequately known, which limits their use in ecological and ecotoxicological studies and handicaps conservation initiatives. We studied the diversity and distribution of amphipods in Switzerland (Central Europe), covering four major drainage basins, an altitudinal gradient of>2,500 m, and various habitats (rivers, streams, lakes and groundwater). We provide the first provisional checklist and detailed information on the distribution and diversity of all amphipod species from Switzerland. In total, we found 29 amphipod species. This includes 16 native and 13 non-native species, one of the latter (Orchestia cavimana) reported here for the first time for Switzerland. The diversity is compared to neighboring countries. We specifically discuss species of the genus Niphargus, which are often receiving less attention. We also found evidence of an even higher level of hidden diversity, and the potential occurrence of further cryptic species. This diversity reflects the biogeographic past of Switzerland, and suggests that amphipods are ideally suited to address questions on endemism and adaptive radiations, post-glaciation re-colonization and invasion dynamics as well as biodiversity-ecosystem functioning relationships in aquatic systems

The future of biotic indices in the ecogenomic era: Integrating (e)DNA metabarcoding in biological assessment of aquatic ecosystems

The bioassessment of aquatic ecosystems is currently based on various biotic indices that use the occurrence and/ or abundance of selected taxonomic groups to define ecological status. These conventional indices have some limitations, often related to difficulties inmorphological identification of bioindicator taxa. Recent development of DNA barcoding and metabarcoding could potentially alleviate some of these limitations, by using DNA sequences instead of morphology to identify organisms and to characterize a given ecosystem. In this paper,we review the structure of conventional biotic indices, andwe present the results of pilotmetabarcoding studies using environmental DNA to infer biotic indices. We discuss the main advantages and pitfalls of metabarcoding approaches to assess parameters such as richness, abundance, taxonomic composition and species ecological values, to be used for calculation of biotic indices.We present some future developments to fully exploit the potential of metabarcoding data and improve the accuracy and precision of their analysis. We also propose some recommendations for the future integration of DNA metabarcoding to routine biomonitoring program

Chytrid epidemics may increase genetic diversity of a diatom spring-bloom

Contrary to expectation, populations of clonal organisms are often genetically highly diverse. In phytoplankton, this diversity is maintained throughout periods of high population growth (that is, blooms), even though competitive exclusion among genotypes should hypothetically lead to the dominance of a few superior genotypes. Genotype-specific parasitism may be one mechanism that helps maintain such high-genotypic diversity of clonal organisms. Here, we present a comparison of population genetic similarity by estimating the beta-dispersion among genotypes of early and peak bloom populations of the diatom Asterionella formosa for three spring-blooms under high or low parasite pressure. The Asterionella population showed greater beta-dispersion at peak bloom than early bloom in the 2 years with high parasite pressure, whereas the within group dispersion did not change under low parasite pressure. Our findings support that high prevalence parasitism can promote genetic diversification of natural populations of clonal hosts